code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {
'''configuration_xlm_roberta''': [
... | 40 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
lowercase : List[str] = """."""
if __name__ == "__main__":
lowercase : List... | 116 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowerCAmelCase__ = pd.read_csv('''sample_data.csv''', header=None)
lo... | 41 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase : int = logging.getLogger(__name__)
class _a (a__ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, A... | 116 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __UpperCamelCase ) -> bool:
lowerCamelCase_ = len(__UpperCamelCase )
# We need to create solution object to save path.
lowerCamelCase_ = [[0 for _ in range(__UpperCamelCase )] for ... | 42 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureE... | 43 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self ,__a = 0 ) -> str:
snake_case : List[Any] = key
def snake_case_... | 116 | 0 |
'''simple docstring'''
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class UpperCAmelCase__ ( A ):
lowerCAmelCase_ = ['image_processor', 'tokenizer']
lowerCAmelCase_ = 'AutoImageProcessor'
lowerCAmelC... | 44 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 116 | 0 |
from math import sqrt
def A ( lowercase__ : int = 100_0000 ) -> int:
UpperCamelCase__ :int = 0
UpperCamelCase__ :int = 0
UpperCamelCase__ :int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , 2 * max_cuboid_size + 1 ):
if sqrt... | 45 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase__ ( __lowercase ):
snake_case : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )
snake_case ... | 116 | 0 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acce... | 46 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 47 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowercase : Tuple = {"""vocab_file""": ""... | 116 | 0 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentPar... | 48 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/autoformer-t... | 116 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : Union[str, Any] = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig... | 49 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutpu... | 116 | 0 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
... | 50 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gp... | 116 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( UpperCAmelCase_ ):
'''simple docstring'''
_lowerCamelCase =(EulerDiscreteSch... | 51 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _a :
'''simple docstring'''
def __init__( self ,__a ,__a ,__a ) -> Tuple:
if dst_width < 0 or... | 116 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...on... | 52 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/pegasus-large""": """https://huggingface.co/... | 116 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 53 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from .... | 116 | 0 |
def a__ ( lowercase__ = 1_0 , lowercase__ = 2_2 ):
'''simple docstring'''
UpperCAmelCase_ =range(1 , lowercase__ )
UpperCAmelCase_ =range(1 , lowercase__ )
return sum(
1 for power in powers for base in bases if len(... | 54 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase : Any = lo... | 116 | 0 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE , unittest.TestCase ):
'''simple docstring'''
... | 55 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Optional[int] = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXCon... | 116 | 0 |
'''simple docstring'''
from __future__ import annotations
def _a (lowercase__ : str ) -> list[int]:
"""simple docstring"""
return [ord(lowercase__ ) - 9_6 for elem in plain]
def _a (lowercase__ : list[int] ) -> str:
"""simple docstring"""
... | 56 |
'''simple docstring'''
def lowerCamelCase__ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
snake_case : int = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__lowercase )
... | 116 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 57 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_sch... | 116 | 0 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_... | 58 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a (metaclass=a__ ):
'''simple docstring'''
lowerCAmelCase_ : Any = ["""flax"""]
def __init__( self ,*__a ,**__a ... | 116 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = ["image_processor", "tokenizer"]
lowercase_ = "CLIPImageProc... | 59 |
'''simple docstring'''
import numpy as np
lowercase : str = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
... | 116 | 0 |
import os
import sys
import unittest
lowerCAmelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_b... | 60 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Union[str, Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 116 | 0 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is... | 61 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_pr... | 116 | 0 |
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
if not all(char in "01" for char in bin_string ):
raise ValueError("Non-binary value was passed to the function" )
if not bin_string:
raise ValueError("Empty string was passed to the function" )
SCREAMING_SNA... | 62 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
lowercase : List[str] = """."""
if __name__ == "__main__":
lowercase : List... | 116 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
a : int = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", ... | 63 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase : int = logging.getLogger(__name__)
class _a (a__ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, A... | 116 | 0 |
from math import pi, sqrt, tan
def A__ ( snake_case_ : float ):
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def A__ ( snake_case_ : float , snake_case_ : float , s... | 64 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__UpperCAmelCase = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
imp... | 65 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self ,__a = 0 ) -> str:
snake_case : List[Any] = key
def snake_case_... | 116 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
UpperCamelCase = pd.read_csv("sample_data.csv", header=None)
UpperCamelCase ... | 66 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 116 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_param... | 67 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase__ ( __lowercase ):
snake_case : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )
snake_case ... | 116 | 0 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class _A ( UpperCamelCase , unit... | 68 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : List[Any] = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
''... | 69 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowercase : Tuple = {"""vocab_file""": ""... | 116 | 0 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_... | 70 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/autoformer-t... | 116 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead."""
)
... | 71 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutpu... | 116 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : str = {
'''xlm-roberta-base''': '... | 72 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gp... | 116 | 0 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
a_ : Any = True
exc... | 73 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _a :
'''simple docstring'''
def __init__( self ,__a ,__a ,__a ) -> Tuple:
if dst_width < 0 or... | 116 | 0 |
def a__ ( snake_case , snake_case ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__SCREAMING_SNAKE_CASE : Dict = str(bin(snake_case ) )[2:] # remove the leading "0b"
__SCREAMIN... | 74 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/pegasus-large""": """https://huggingface.co/... | 116 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 75 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from .... | 116 | 0 |
"""simple docstring"""
import collections
import importlib.util
import os
import re
from pathlib import Path
a_ = 'src/transformers'
# Matches is_xxx_available()
a_ = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
a_ ... | 76 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase : Any = lo... | 116 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision... | 77 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Optional[int] = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXCon... | 116 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ : list[int | float] , snake_case_ : int , snake_case_ : int ) -> int | float:
'''simple docstring'''
if len(snake_case_ ) == 0:
ra... | 78 |
'''simple docstring'''
def lowerCamelCase__ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
snake_case : int = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__lowercase )
... | 116 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.c... | 79 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_sch... | 116 | 0 |
def snake_case ( lowerCamelCase = 1_000 ):
'''simple docstring'''
__lowercase = 2**power
__lowercase = str(lowerCamelCase )
__lowercase = list(lowerCamelCase )
__lowercase = 0
for i in list_num:
sum_of_num += int(lowerCamelCase ... | 80 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a (metaclass=a__ ):
'''simple docstring'''
lowerCAmelCase_ : Any = ["""flax"""]
def __init__( self ,*__a ,**__a ... | 116 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import torch
if is_vision_availab... | 81 |
'''simple docstring'''
import numpy as np
lowercase : str = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
... | 116 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 82 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Union[str, Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 116 | 0 |
"""simple docstring"""
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common i... | 83 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_pr... | 116 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 84 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
lowercase : List[str] = """."""
if __name__ == "__main__":
lowercase : List... | 116 | 0 |
def _a ( lowercase__ : int , lowercase__ : int ):
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def _a ( ):
'''simple docstring'''
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert ... | 85 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase : int = logging.getLogger(__name__)
class _a (a__ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, A... | 116 | 0 |
from __future__ import annotations
class _a :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : str , UpperCAmelCase : str ):
A_ , A_ = text, pattern
A_ , A_ = l... | 86 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[str]:
"""simple docstring"""
def wrapper(*lowercase_ , **lowercase_ ):
... | 87 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self ,__a = 0 ) -> str:
snake_case : List[Any] = key
def snake_case_... | 116 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE , **S... | 88 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 116 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE : str = {
"configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}
try:
if not is_torch_available()... | 89 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase__ ( __lowercase ):
snake_case : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )
snake_case ... | 116 | 0 |
'''simple docstring'''
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger(__name__)
def ... | 90 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats... | 91 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowercase : Tuple = {"""vocab_file""": ""... | 116 | 0 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __magic_name__ : str ) -> str:
lowercase : Tuple =''''''
try:
with open(__magic_name__ , '''rb''' ) as binary_file:
lowercase : Dict =binary_f... | 92 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/autoformer-t... | 116 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_rober... | 93 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutpu... | 116 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE = {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}
try:
if not is_vision_avail... | 94 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gp... | 116 | 0 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class UpperCamelCase_ (nn.Module ):
def __init__( self : int , lowerCAmelCase_ : int = 16 , lowerCAmelCase_ : ... | 95 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _a :
'''simple docstring'''
def __init__( self ,__a ,__a ,__a ) -> Tuple:
if dst_width < 0 or... | 116 | 0 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
cla... | 96 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/pegasus-large""": """https://huggingface.co/... | 116 | 0 |
import os
def a ( ):
'''simple docstring'''
with open(os.path.dirname(snake_case__ ) + '''/grid.txt''' ) as f:
lowercase_ = [] # noqa: E741
for _ in range(20 ):
l.append([int(snake_case__ ) for x in f.readline().split()] )
lo... | 97 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from .... | 116 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Dict = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.j... | 98 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase : Any = lo... | 116 | 0 |
SCREAMING_SNAKE_CASE = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
SCREAMING_SNAKE_CA... | 99 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Optional[int] = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXCon... | 116 | 0 |
def __snake_case ( lowerCAmelCase_ = 1_0_0 ) -> int:
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ ... | 100 |
'''simple docstring'''
def lowerCamelCase__ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
snake_case : int = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__lowercase )
... | 116 | 0 |
from __future__ import annotations
def a__ ( A__, A__, A__, A__ ):
SCREAMING_SNAKE_CASE_ : List[Any] = []
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Union[str, Any] = input_list[low:mid], input_list[mid : high + 1]
while le... | 101 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_sch... | 116 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObject... | 102 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a (metaclass=a__ ):
'''simple docstring'''
lowerCAmelCase_ : Any = ["""flax"""]
def __init__( self ,*__a ,**__a ... | 116 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP... | 103 |
'''simple docstring'''
import numpy as np
lowercase : str = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
... | 116 | 0 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Sessio... | 104 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Union[str, Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 116 | 0 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def __UpperCAmelCase ( lowerCamelCase_ : Any , lowerCamelCase_ : Tuple ) -> Tuple:
"""simple do... | 105 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_pr... | 116 | 0 |
import math
def lowerCamelCase_ ( lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : List[str] ) -> List[Any]:
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.l... | 106 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
lowercase : List[str] = """."""
if __name__ == "__main__":
lowercase : List... | 116 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import ... | 107 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase : int = logging.getLogger(__name__)
class _a (a__ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, A... | 116 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__a: str = logging.get_logger(__name__)
__a: Union[st... | 108 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
a = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str,... | 109 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self ,__a = 0 ) -> str:
snake_case : List[Any] = key
def snake_case_... | 116 | 0 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAuto... | 687 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 116 | 0 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __a ( _UpperCamelCase: Any ) -> List[str]:
"""simple docstring"""
_snake_case = prime_factors(__lowercase )
if is_square_free(... | 185 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase__ ( __lowercase ):
snake_case : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )
snake_case ... | 116 | 0 |
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load_datase... | 654 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowercase : Optional[Any] =logging.get_logger(__name__)
__l... | 54 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowercase : Tuple = {"""vocab_file""": ""... | 116 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import Attention... | 634 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/autoformer-t... | 116 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Da... | 502 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutpu... | 116 | 0 |
'''simple docstring'''
import os
import sys
UpperCAmelCase_ = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
... | 539 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gp... | 116 | 0 |
def __magic_name__ ( __lowerCAmelCase : Union[str, Any] , __lowerCAmelCase : Optional[int] , __lowerCAmelCase : List[Any] , __lowerCAmelCase : List[Any] ) -> List[str]:
if height >= 1:
move_tower(height - 1 , __lowercase , __... | 298 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _a :
'''simple docstring'''
def __init__( self ,__a ,__a ,__a ) -> Tuple:
if dst_width < 0 or... | 116 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
A_ : Optional[int] ={"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCH... | 483 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/pegasus-large""": """https://huggingface.co/... | 116 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _A ( snake_case__ : Optional[int] ):
snake_case__ : Tuple = SwinConfig(image_size=1_92 )
if... | 261 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from .... | 116 | 0 |
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE = (
((5, 2, 3), 1_5),
((6, 5, 9), 2_5),
((1_1, 1_2, 1_3), 4_1),
((1, 1, 1), 8),
((1_1, 1_2, 1_3), 4_1),
)
SCREAMING_SNAKE_CASE = (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, 3_5, 4_9), 1_5_0))
SC... | 99 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase : Any = lo... | 116 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from tr... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Optional[int] = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXCon... | 116 | 0 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_avai... | 185 |
'''simple docstring'''
def lowerCamelCase__ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
snake_case : int = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__lowercase )
... | 116 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a__ = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptTokenizer"""],
}
... | 654 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_sch... | 116 | 0 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__lowercase : Optional[int] ="""\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
... | 54 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a (metaclass=a__ ):
'''simple docstring'''
lowerCAmelCase_ : Any = ["""flax"""]
def __init__( self ,*__a ,**__a ... | 116 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase : List[str] = argparse.ArgumentParser()
parser.add_argu... | 634 |
'''simple docstring'''
import numpy as np
lowercase : str = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
... | 116 | 0 |
'''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import... | 502 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Union[str, Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 116 | 0 |
'''simple docstring'''
UpperCAmelCase_ = {
0: """0""",
1: """1""",
2: """2""",
3: """3""",
4: """4""",
5: """5""",
6: """6""",
7: """7""",
8: """8""",
9: """9""",
10: """a""",
11: """b""",
12: """c""",
13: """d""",
14: """e"... | 539 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_pr... | 116 | 0 |
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
SCREAMING_SNAKE_CASE__ : int = """facebook/wmt19-en-de"""
SCREAMING_SNAKE_CASE__ : Dict = FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master model
SCREAMING_SNAKE_CA... | 298 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
lowercase : List[str] = """."""
if __name__ == "__main__":
lowercase : List... | 116 | 0 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
A_ : Any ... | 483 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase : int = logging.getLogger(__name__)
class _a (a__ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, A... | 116 | 0 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _A ( snake_case__ : Optional[Any] ):
snake_case__ : List[Any] = FileLock(str(tmpdir / '''foo.lock''' ) )
snake_case__ : str = FileLo... | 261 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
from __future__ import annotations
class __UpperCAmelCase :
"""simple docstring"""
def __init__( self , __A = 0 ):
__a = key
def snake_case_ ( self , __A , __A ):
assert isinstance(__a , __a ) and isinstance... | 99 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self ,__a = 0 ) -> str:
snake_case : List[Any] = key
def snake_case_... | 116 | 0 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import Vi... | 687 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 116 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a ( metaclass=a__ ):
SCREAMING_SNAKE_CASE_ : Dict = ["""onnx"""]
def __init__( self ,*_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE ) -> Optional[int]:
... | 185 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase__ ( __lowercase ):
snake_case : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )
snake_case ... | 116 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipelin... | 654 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class A :
def __init__( self: int , _lowerCAmelCase: Any , _lowerCAmelCase: List[Any] , _lowerCAmelCase: Optional[Any] ) -> Tuple:
'''simple docstring'''
... | 54 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowercase : Tuple = {"""vocab_file""": ""... | 116 | 0 |
'''simple docstring'''
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class A ( a__ , a__ ):
__magic_name__ ... | 634 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/autoformer-t... | 116 | 0 |
'''simple docstring'''
from typing import Any
import numpy as np
def _lowerCAmelCase ( lowerCamelCase_ : Dict ):
return np.array_equal(__lowercase , matrix.conjugate().T )
def _lowerCAmelCase ( lowerCamelCase_ : List[str] , lowe... | 502 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutpu... | 116 | 0 |
'''simple docstring'''
class __lowercase :
def __init__( self ) -> str:
__a = 0
__a = 0
__a = {}
def UpperCamelCase__ ( self , UpperCamelCase ) -> Optional[int]:
... | 539 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gp... | 116 | 0 |
from collections import Counter
from timeit import timeit
def __magic_name__ ( __lowerCAmelCase : str = "" , ) -> List[Any]:
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def __magic_name__ ( __lowerCA... | 298 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _a :
'''simple docstring'''
def __init__( self ,__a ,__a ,__a ) -> Tuple:
if dst_width < 0 or... | 116 | 0 |
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